1 citations · 3 across the 16 of their papers we have counts for
16 papers
Adapting Vision Foundation Models to Acoustics for Pose-Free 3D Sonar Reconstruction
Kevin Zhang, Jingxi Chen, Mohamad Qadri +5
Vision foundation models trained on Internet-scale RGB datasets enable remarkable capabilities across a range of tasks, from text-to-video generation to few-shot 3D scene reconstru…
-VLA: a Hierarchical Robot Foundation Model with World-Model-Guided Test-Time Computation
Xiaowei Cai, Yunuo Cai, Bingao Chen +36
Long-horizon robot manipulation requires a robot to both execute individual skills reliably and sequence them coherently over extended tasks. Most hierarchical vision-language-acti…
COMFYCLAW: Self-Evolving Skill Harnesses for Image Generation Workflows
Zongxia Li, Dawei Liu, Fuxiao Liu +6
Agents are increasingly used to construct workflows and assist humans in completing recurring tasks more efficiently. As these workflows become repeated and domain-specific, agent…
From Inpainting to Layer Decomposition: Repurposing Generative Inpainting Models for Image Layer Decomposition
Jingxi Chen, Yixiao Zhang, Xiaoye Qian +4
Images can be viewed as layered compositions, foreground objects over background, with potential occlusions. This layered representation enables independent editing of elements, of…
MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models
Xiyang Wu, Zongxia Li, Jihui Jin +7
Vision Language Models (VLMs) perform well on standard video tasks but struggle with physics-related reasoning involving motion dynamics and spatial interactions. We present a nove…
First Frame Is the Place to Go for Video Content Customization
Jingxi Chen, Zongxia Li, Zhichao Liu +6
What role does the first frame play in video generation models? Traditionally, it's viewed as the spatial-temporal starting point of a video, merely a seed for subsequent animation…
Learning Normal Flow Directly From Event Neighborhoods
Dehao Yuan, Levi Burner, Jiayi Wu +4
Event-based motion field estimation is an important task. However, current optical flow methods face challenges: learning-based approaches, often frame-based and relying on CNNs, l…
Repurposing Pre-trained Video Diffusion Models for Event-based Video Interpolation
Jingxi Chen, Brandon Y. Feng, Haoming Cai +6
Video Frame Interpolation aims to recover realistic missing frames between observed frames, generating a high-frame-rate video from a low-frame-rate video. However, without additio…
Active Human Pose Estimation via an Autonomous UAV Agent
Jingxi Chen, Botao He, Chahat Deep Singh +2
One of the core activities of an active observer involves moving to secure a "better" view of the scene, where the definition of "better" is task-dependent. This paper focuses on t…
CodedEvents: Optimal Point-Spread-Function Engineering for 3D-Tracking with Event Cameras
Sachin Shah, Matthew Albert Chan, Haoming Cai +5
Point-spread-function (PSF) engineering is a well-established computational imaging technique that uses phase masks and other optical elements to embed extra information (e.g., dep…
Microsaccade-inspired Event Camera for Robotics
Botao He, Ze Wang, Yuan Zhou +11
Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. Th…
TimeRewind: Rewinding Time with Image-and-Events Video Diffusion
Jingxi Chen, Brandon Y. Feng, Haoming Cai +4
This paper addresses the novel challenge of ``rewinding'' time from a single captured image to recover the fleeting moments missed just before the shutter button is pressed. This p…
ConVRT: Consistent Video Restoration Through Turbulence with Test-time Optimization of Neural Video Representations
Haoming Cai, Jingxi Chen, Brandon Y. Feng +5
tmospheric turbulence presents a significant challenge in long-range imaging. Current restoration algorithms often struggle with temporal inconsistency, as well as limited generali…
ProxMaP: Proximal Occupancy Map Prediction for Efficient Indoor Robot Navigation
Vishnu Dutt Sharma, Jingxi Chen, Pratap Tokekar
In a typical path planning pipeline for a ground robot, we build a map (e.g., an occupancy grid) of the environment as the robot moves around. While navigating indoors, a ground ro…
ProxMaP: Proximal Occupancy Map Prediction for Efficient Indoor Robot Navigation
Vishnu Dutt Sharma, Jingxi Chen, Pratap Tokekar
Planning a path for a mobile robot typically requires building a map (e.g., an occupancy grid) of the environment as the robot moves around. While navigating in an unknown environm…
Multi-Agent Deep Reinforcement Learning For Persistent Monitoring With Sensing, Communication, and Localization Constraints
Manav Mishra, Prithvi Poddar, Rajat Agarwal +3
Determining multi-robot motion policies for persistently monitoring a region with limited sensing, communication, and localization constraints in non-GPS environments is a challeng…